scholarly journals Non‐asymptotic moment bounds for random variables rounded to non‐uniformly spaced sets

Stat ◽  
2021 ◽  
Author(s):  
Tyler Chen
Keyword(s):  
Random Variables ◽  
Moment Bounds

Moment bounds for non-stationary dependent sequences

1994 ◽  
Vol 31 (3) ◽  
pp. 731-742 ◽  
Author(s):  
Tae Yoon Kim
Keyword(s):  
Random Variables ◽  
Partial Sums ◽  
Unified Approach ◽  
Dependent Random Variables ◽  
Combinatorial Argument ◽  
Stationarity Condition ◽  
Weakly Dependent Random Variables ◽  
Mixing Sequences ◽  
Moment Bounds ◽  
Weakly Dependent

We provide a unified approach for establishing even-moment bounds for partial sums for a class of weakly dependent random variables satisfying a stationarity condition. As applications, we discuss moment bounds for various types of mixing sequences. To obtain even-moment bounds, we use a ‘combinatorial argument' developed by Cox and Kim (1990).

Comparison Between the Chernoff and Factorial Moment Bounds for Discrete Random Variables

1997 ◽  
Vol 51 (1) ◽  
pp. 40 ◽  
Author(s):  
Philippe Naveau
Keyword(s):  
Factorial Moment ◽  
Random Variables ◽  
Discrete Random Variables ◽  
Moment Bounds

Moment bounds for non-stationary dependent sequences

1994 ◽  
Vol 31 (03) ◽  
pp. 731-742 ◽  
Author(s):  
Tae Yoon Kim
Keyword(s):  
Random Variables ◽  
Partial Sums ◽  
Unified Approach ◽  
Dependent Random Variables ◽  
Combinatorial Argument ◽  
Stationarity Condition ◽  
Weakly Dependent Random Variables ◽  
Mixing Sequences ◽  
Moment Bounds ◽  
Weakly Dependent

We provide a unified approach for establishing even-moment bounds for partial sums for a class of weakly dependent random variables satisfying a stationarity condition. As applications, we discuss moment bounds for various types of mixing sequences. To obtain even-moment bounds, we use a ‘combinatorial argument' developed by Cox and Kim (1990).

Moment bounds for truncated random variables

2009 ◽  
Vol 79 (18) ◽  
pp. 1951-1956 ◽  
Author(s):  
Guoqing Liu ◽  
Wenbo V. Li
Keyword(s):  
Random Variables ◽  
Moment Bounds

Normal approximations to discrete unimodal distributions

1986 ◽  
Vol 23 (04) ◽  
pp. 1013-1018
Author(s):  
B. G. Quinn ◽  
H. L. MacGillivray
Keyword(s):  
Stationary Distribution ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Hypergeometric Distribution ◽  
Death Process ◽  
Normal Approximations ◽  
Discrete Random Variables ◽  
Birth Death

Sufficient conditions are presented for the limiting normality of sequences of discrete random variables possessing unimodal distributions. The conditions are applied to obtain normal approximations directly for the hypergeometric distribution and the stationary distribution of a special birth-death process.

Random Variables

1989 ◽  
Keyword(s):  
Random Variables
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